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DBMS > Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. SurrealDB vs. TiDB

System Properties Comparison Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. SurrealDB vs. TiDB

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  Xexclude from comparisonTiDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMSTiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
Primary database modelRelational DBMS infocolumn orientedSearch engineRelational DBMSDocument store
Graph DBMS
Relational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score4.25
Rank#74  Overall
#40  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorersphinxsearch.comsplicemachine.comsurrealdb.compingcap.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-workssurrealdb.com/­docsdocs.pingcap.com/­tidb/­stable
DeveloperMicrosoftSphinx Technologies Inc.Splice MachineSurrealDB LtdPingCAP, Inc.
Initial release20192001201420222016
Current releasecloud service with continuous releases3.5.1, February 20233.1, March 2021v1.5.0, May 20248.1.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.
Implementation languageC++JavaRustGo, Rust
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesschema-freeyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesno
Secondary indexesall fields are automatically indexedyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yesSQL-like query languageyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyes infoJavano
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning (by key range)
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoYes, via Full Spark Integrationnoyes infowith TiSpark Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infofull support since version 6.6
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAzure Active Directory AuthenticationnoAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesFine grained access rights according to SQL-standard
More information provided by the system vendor
Microsoft Azure Data ExplorerSphinxSplice MachineSurrealDBTiDB
Specific characteristicsTiDB is an advanced open-source, distributed SQL database for modern application...
» more
Competitive advantages- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
» more
Typical application scenariosTiDB is ideal for transactional applications that require extreme scalability and...
» more
Key customersBlock, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more
Market metrics34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more
Licensing and pricing modelsTiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : Enterprise...
» more

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More resources
Microsoft Azure Data ExplorerSphinxSplice MachineSurrealDBTiDB
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